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Web Performance Measurement and Storytelling

1 post · Aug 2022

What this trail covers

Spotify's approach to web performance measurement and storytelling has evolved to emphasize the critical role of data in demonstrating the value of performance improvements. This includes leveraging lab data from tools like Lighthouse CI for early feedback on pull requests and integrating real user data from sources like Google Analytics into dashboards for monitoring performance in production. The focus is on using core Web Vitals metrics (LCP, FID, CLS) and other supported metrics (FCP, TTFB, INP) to identify areas for improvement, validate the impact of changes, and build a compelling narrative for stakeholders. This iterative process, combining lab and field data, allows for targeted optimizations and a better understanding of the user experience.

All Spotify trails
  1. From Development to Real Users: How to Create a Web Performance StoryThis post details Spotify's methodology for creating a 'web performance story' by combining lab and real user data. It introduces the use of Lighthouse CI integrated into Backstage for pull request feedback, emphasizing its role in comparing metrics against master and visualizing trends. The post highlights the necessity of field data to complement lab data and discusses key Web Vitals metrics (LCP, FID, CLS) and other supported metrics (FCP, TTFB, INP). It also describes the integration of Google Analytics export to BigQuery for real-time monitoring dashboards and presents a case study of Server Side Rendering (SSR) for the mobile web player to illustrate how data validates performance improvements and guides further investigation.